--- source_url: "https://karatelabs.io/?utm_source=openai" title: "Karate Labs - Unified API, UI & AI Test Automation" mirrored_at: 2026-08-10T01:08:45.239Z host: karatelabs.io cited_in_42a: true mirror_canonical: "https://index.42a.ai/karatelabs.io/index__q__utm_source_openai" --- > **Original source:** https://karatelabs.io/?utm_source=openai The quality governance platform for AI-built software **Generation got cheap. Knowing what’s safe to ship didn’t.** Karate governs it, on the open-source engine trusted by 76 of the Fortune 500. Open-source API, UI & AI test automation One engine for API, UI & AI testing. **Write 60% less test code**, run it in any CI, and drive the browser with any LLM you host, DOM-first, MCP-native, self-hosted. Open core, 8.9k★ on GitHub. [Featured in the Gartner® Market Guide · API & MCP Testing Tools](https://www.gartner.com/reviews/market/api-and-mcp-testing-tools) The Problem ## Testing is fragmented, slow, and painful Different tools for API tests, UI tests, mocks, and performance Verbose code that takes longer to write than the feature itself Tests that break every time you refactor, slowing your team down The problem, in your language ## “All green” is not the same as “proven.” A passing dashboard reports **activity**. Your board, your auditors, and your regulators ask for **assurance**. Those are not the same question. What the dashboard counts - •Endpoints hit, tests passed, percent green - •“100% of operations exercised” - •A build that went green last night Activity. It tells you something ran. What an auditor asks - •Which business rule did we actually prove? - •Was the senior-driver, high-risk-claim, boundary case exercised, or only claimed? - •Where is the evidence, and is it safe to ship? Assurance. It tells you you’re safe to ship. When the same AI writes the code _and_ its tests, passing becomes the goal instead of finding the flaw. **“100% hit” can still be not ready to ship.** For product owners · author of intent ## One rulebook. Two readers. One verdict. You define what “correct” means, in plain business terms. That one definition becomes the **test** that verifies it, the **mock** that stands in for a system that isn’t ready, and the **evidence** an auditor will accept. One artifact, not a report you sign off after the fact. Product Owner defines & approves → Review a decision table, not code Requirements go in; the agent drafts the rule; you see it as a decision table and a flowchart: gaps, negative cases, and boundaries surfaced. You approve; it’s committed to version control. Your approval is the gate. → Developer consumes as-is One source of truth, two readers The same rule your engineers run as an executable oracle and a mock. No translation to a second spec, no drift between what you meant and what shipped. [The same rule, run by engineering](https://karatelabs.io/trust-governance?persona=technical) The oracle It computes the expected result, so no one hand-codes assertions that drift from what you meant. The mock It stands in for a backend that isn’t built yet, so verification doesn’t wait on another team. Traceability Every rule carries a requirement ID, so coverage tracks back to the requirement you signed off, as audit evidence. **AI proposes. Deterministic verification decides.** The agent explores the system, finds scenarios no one covered, and drafts candidate rules in plain language. Then a deterministic check grades every claim against the rule you approved, with no model in the path and nothing to second-guess. [Featured in the Gartner® Market Guide · API & MCP Testing Tools](https://www.gartner.com/reviews/market/api-and-mcp-testing-tools) The bottom line for a product owner READY CONDITIONAL NOT-READY ## Is it safe to ship? Computed, not guessed. Every release gets a verdict, graded against the business rules you defined, with the blockers named and the evidence attached. No model in the path. The answer you can take to your board, or an auditor. [See how it’s computed](https://karatelabs.io/trust-governance) [See how your rule produces it](#author-of-intent) Proof, not a promise ## We publish our own failing grade. Our reference API, graded by our own tooling, in public, on every commit. No login, no demo request. Deterministic. No model produced any of it, so anyone can re-derive it. [How it is computed](https://karatelabs.io/api-governance). Open core · the engine ## Every kind of test, one framework. Under all three pillars is the open-source engine teams already trust: API, UI, mocks, and performance in one syntax. See the Difference ## Write 60% less test code Traditional (RestAssured): 25 lines ``` import io.restassured.RestAssured; import static io.restassured.RestAssured.*; import static org.hamcrest.Matchers.*; public class UserTest { @Test public void testCreateUser() { RestAssured.baseURI = "https://api.example.com"; String body = "{" + "\"name\": \"John\"," + "\"email\": \"john@test.com\"" + "}"; given() .contentType("application/json") .body(body) .when() .post("/users") .then() .statusCode(201) .body("name", equalTo("John")) .body("id", notNullValue()); } } ``` ``` import org.openqa.selenium.*; import org.openqa.selenium.chrome.*; import org.openqa.selenium.support.ui.*; public class LoginTest { @Test public void testLogin() { WebDriver driver = new ChromeDriver(); try { driver.get("https://app.example.com"); WebDriverWait wait = new WebDriverWait( driver, Duration.ofSeconds(10)); driver.findElement(By.id("email")) .sendKeys("test@test.com"); driver.findElement(By.id("password")) .sendKeys("secret"); driver.findElement(By.cssSelector( "button[type='submit']")).click(); wait.until(ExpectedConditions .presenceOfElementLocated( By.className("dashboard"))); } finally { driver.quit(); } } } ``` With Karate: 8 lines ``` Feature: User API Scenario: Create a new user Given url 'https://api.example.com/users' And request { name: 'John', email: 'john@test.com' } When method post Then status 201 And match response.name == 'John' And match response.id == '#notnull' ``` ``` Feature: Login Flow Scenario: User logs in successfully Given driver 'https://app.example.com' And input('#email', 'test@test.com') And input('#password', 'secret') When click("button[type='submit']") Then waitFor('.dashboard') ``` New · AI Test Automation ## Karate Agent, the AI-native test workspace, built into the platform. An LLM-powered agent that drives the browser, recovers when UIs drift, and authors tests in plain English. **Display-text locators**, **BYO LLM** (Claude, GPT, Gemini, Llama, Ollama), **100% self-hosted**, and **MCP-native** for Claude Code and VS Code Copilot. Scripted flow runtime (vs 8–19 min pure-LLM) Fewer page scans (lower token cost) Tokens on scripted paths (LLM only on recovery) Faster test authoring Less code vs alternatives Faster with parallel execution Recognized by analysts, reviewers & developers Enterprise Ready ## Built for scale. Designed for teams. Everything your organization needs to adopt test automation at scale, with enterprise-grade security and support. ### Single-tenant by design One isolated instance per team, behind your firewall. No shared identity store, no multi-tenant attack surface. ### Role-Based Access Fine-grained permissions for teams, projects, and environments. ### Audit Logs Complete visibility into who did what, when. Export-ready for compliance. ### Local-First by Design Self-hosted end-to-end. No SaaS dependency, no telemetry, no outbound calls. Your data never leaves your network. ### Dedicated Support Named account manager, SLA-backed response times, and onboarding assistance. ### Self-Hosted Option Deploy in your own cloud or on-premise. Your data never leaves your infrastructure. [Talk to Sales](https://karatelabs.io/contact-us#sales) [Featured in the Gartner® Market Guide · API & MCP Testing Tools](https://www.gartner.com/reviews/market/api-and-mcp-testing-tools) What Teams Are Saying ## Loved by developers. Trusted by enterprises. “Ease of setup, ease of writing tests even for juniors, and the fact that it uses Gherkin allows everyone to understand the tests.” LK “Well documented and well supported. The DSL is so simple to learn. Offers a full range of automation capabilities: client-side assertions, server-side mocks and simulators, even performance testing.” AS “An excellent tool in all sense. Used it for both API and UI automation. Found it amazing with parallel execution, negligible flakiness, and code-less automation.” KJ Questions ## The things people ask first Is Karate a cloud service? No. Everything runs on your machines, your CI, your environments. No hosted tier, no test grid, no telemetry. Payloads and secrets never leave your infrastructure, which is why Karate runs air-gapped in financial services, insurance and healthcare. What does Karate test? APIs across REST, GraphQL, SOAP, gRPC, Kafka and WebSocket, plus browser and desktop UI, performance and mocking. One syntax, so the same file drives a functional test, a load test and a contract test without a rewrite. How is this different from a passing test suite? A passing suite reports activity. It does not say which business rule was proved, whether the risky case was exercised or only claimed, or whether the only thing answering was your own mock. Karate joins evidence to requirements and computes a verdict, with blockers named. Is any of the scoring done by an AI model? No. Verdicts are deterministic: no model, no network, no guess. Same inputs, same result, so an auditor can re-derive it. AI helps author tests, never decides whether one passed. Can we use our own LLM? Yes. Bring your own model, including self-hosted via Ollama, so the pipeline runs inside your perimeter with no outbound calls. Model choice is config, not a different product. Do we have to replace the tests we already have? No. Teams adopt incrementally: new tests in Karate, existing suites carry on. The platform layers governance and coverage on top of what you have. [119 more answers for technical and procurement teams](https://karatelabs.io/enterprise-evaluation) Get Started ## Start where it suits you. ### Open source. Community driven. Join thousands of developers who contribute to and rely on Karate every day. Star us on GitHub, submit a PR, or just say hello. 8,834+ GitHub Stars 350+ Contributors 2M+ Downloads ### Enterprise Platform Audit logs, offline licensing, and dedicated support. 100% local. Your data never leaves your infrastructure. Air-gap ready Self-hosted